"I am a computational social and behavioral scientist with broad interests in social behavior, media effects, human-AI communication, and wellbeing."
I am currently an Assistant Adjunct Professor in the Department of Computational Media at the University of California, Santa Cruz, and a Stanford Affiliate in the Department of Communication at Stanford University. I received my Ph.D. in Computer Science from the University of Colorado, Boulder.
I am a computational social and behavioral scientist with broad interests in social behavior, Media Effects, Human-AI Communication, and Wellbeing. My research sits at the intersection of data science, psychology, communication. I look at three connected questions:
How do everyday interactions affect our emotions and social wellbeing? For example, does it matter whether you talk to a close friend in person versus over text? Does where you are, or who you're with, change how meaningful an interaction feels?
Can we predict psychological and emotional wellbeing from everyday social and communication behavior? I use behavioral data — like patterns in messages, calls, or even physical movement — to build models that estimate people's psychological states.
How is talking to an AI different from talking to a person, and does it help or hurt us? As AI chatbots and assistants become more common, I study whether these interactions can support people's emotional and social needs the way human relationships do, or whether they fall short (or even cause harm) in ways we should be careful about.
Across all of this, I'm interested in how factors like who you're talking to, where you are, and even individual personality differences change these patterns.
My path started in computer science, but I was always drawn to questions about human behavior. During my Ph.D., I applied machine learning methods to predict momentary emotional states — that was the first bridge between computational methods and psychological questions.
A bigger shift happened later, when I moved into postdoctoral training in psychology. Transitioning from a computer science background into psychology and HCI was a significant change, and honestly it took longer to adjust than I expected — the questions, research methods, and even the way you argue for evidence are quite different across these fields. Looking back, I think if I had taken some humanities or social science coursework during my BS, it might have prepared me for this transition sooner since I was already intellectually drawn in that direction without having the formal grounding for it yet.
My research then began to focus on social interaction and wellbeing — understanding how our everyday interactions with others shape emotional and social outcomes. Given my computer science background, extending this work to human-AI interaction felt like a natural continuation an extension of that same interest into a new and increasingly important relational context.
"Some of the most impactful pivots in research come not from having more resources, but from looking at what you already have through a new lens."
One of the most rewarding moments in my research came unexpectedly. I had been thinking for a while about how to transition my research toward AI, and I had several ideas in mind, but nearly all of them would have required new data collection. This meant time and resources I didn't yet have. Then, during a flight, it suddenly clicked: I already had a dataset that could be repurposed to study this question through the lens of AI. That "airplane moment" turned into a paper that ended up getting a lot of attention, and it became the foundation that redirected a major part of my research program toward human-AI communication.
What made it so exciting wasn't just the excitement of the idea itself, but realizing that a resourceful reframing of existing data — rather than waiting for the "ideal" new dataset — could open up an entirely new research direction. It taught me that some of the most impactful pivots in research come not from having more resources, but from looking at what you already have through a new lens.
My career goal since childhood has been to become a professor, and becoming an assistant professor is the next step toward that goal.
I'd tell them that we are truly a multidisciplinary lab, with students coming from different backgrounds. If you're coming from a non-traditional background, as I did myself, that's not a disadvantage; it's often an asset, since some of the most interesting research questions live at the intersections between fields.
Our mentor is genuinely supportive, and the lab is set up to help students grow rather than just produce output. You'd have access to strong computational resources, and the chance to collaborate not only within the lab but also with HCI students and other UC scholars.